Manage your subscription

Program can tell when the face fits

By BOB HOLMES

Computer imaging’s toughest case – matching the face with the photograph
– could have been solved by researchers at the Massachusetts Institute of
Technology. With this ability, computers could rapidly scan a database of
photographs to identify suspected criminals, verify a passport or perform
other tasks that involve tedious and time-consuming manual searches.

Recognising faces is easy for people, but it has long seemed an almost
insurmountable problem for computers. Most computer recognition techniques
measure the relative positions of specific facial features and then compare
them. But this approach cannot cope with the wide variety of facial expressions,
view angles and lighting conditions found in photos.

In the past few years, however, computer scientist Alex Pentland and
his colleagues at MIT have tried a new tack. Pentland analysed several hundred
photos of different faces. The pixels that make up these photos vary in
light and shade. Pentland calculated the average brightness of each pixel
to create a ‘typical’ face. He then let the computer define dozens of different
statistical ways in which individual photographs deviated from the norm.
Six of these differences are needed to identify individuals.

When the program is confronted with the photograph of a face, it first
aligns it with the norm, then calculates the values of the six ways in which
the photograph differs from it. After that, the program simply compares
these statistical values with ones in its database of photographs and picks
out the best match. The technique can pick the correct face from a set of
more than 7500 photos with 95 per cent accuracy in less than a second, says
Pentland.

Advertisement

For the easier task of verifying that two photos of the same person
match, its accuracy tops 99.9 per cent – making it as reliable as other
systems of verifying identity such as voiceprints, fingerprints or retinal
patterns.

Pentland also constructed norms for eyes, noses and mouths, and selected
meaningful deviations in the same way he did for whole faces. By combining
this single-feature recognition with the whole- face method, the computer
found correct matches even if a person wore sunglasses in one photo or if
part of the face was hidden. In one case, the computer correctly matched
two photos of the same individual, one with a beard and one without.

The new technology has been patented, and practical applications are
being developed. The Mexican government is considering using it to maintain
voting records, says Pentland. The same basic technique could also be used
to match other images, such as fabric patterns. No ‘ quick fix’ for climate